Skip to contents

Life Cycle Status R-CMD-check codecov DOI Binder


The main goal of developing this package is to construct an R-based front-end to connect to a variety of highly used TASSEL methods and analytical tools. By using R as a front-end, we aim to utilize a unified scripting workflow that exploits the analytical prowess of TASSEL in conjunction with R’s popular data handling and parsing capabilities without ever having the user to switch between these two environments. rTASSEL also provide feature and speed advantages compared to other commonly used R packages. Take a look here for more information.


To cite rTASSEL, please use the following citation:

Monier et al., (2022). rTASSEL: An R interface to TASSEL for analyzing genomic diversity. Journal of Open Source Software, 7(76), 4530,


If you want to test out what this package does but do not want to install it locally, we have set up an interactive Jupyter notebook detailing the walkthrough of rTASSEL on Binder. The Binder link can be accessed through the Binder icon on this page or by clicking here.

Installation and usage

If you do not have experience working with and setting up rJava with your R installation, it is recommended that you read the long-form documentation. This walkthrough can be found here. If you are already fairly comfortable working with Java JDK and rJava, you can follow the following commands.

Package source code can be installed directly from this BitBucket repository using the devtools package:

if (!require("devtools")) install.packages("devtools")

Vignettes (build_vignettes) are optional since there are constantly updated article links on our website. If you do want to build vignettes locally, please use the following instructions:

if (!require("devtools")) install.packages("devtools")
    repo = "maize-genetics/rTASSEL",
    ref = "master",
    build_vignettes = TRUE,
    dependencies = TRUE

Getting help

For an overview of available functions, use the following command:

help(package = "rTASSEL")

If you need a walkthrough for potential pipelines, long-form documentation can be found on our website including a getting started article.

If you would like to study a function in full, refer to the R documentation by using ?<function> in the console, where <function> is an rTASSEL-based function.